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Scaling up high throughput field phenotyping of corn and soy research plots using ground rovers

机译:使用地面舷梯扩展玉米和大豆研究情节的高吞吐场表型

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Crop improvement programs require large and meticulous selection processes that effectively and accurately collect and analyze data to generate quality plant products as efficiently as possible, develop superior cropping and/or crop improvement methods. Typically, data collection for such testing is performed by field teams using hand-held instruments or manually-controlled devices. Although steps are taken to reduce error, the data collected in such manner can be unreliable due to human error and fatigue, which reduces the ability to make accurate selection decisions. Monsanto engineering teams have developed a high-clearance mobile platform (Rover) as a step towards high throughput and high accuracy phenotyping at an industrial scale. The rovers are equipped with GPS navigation, multiple cameras and sensors and on-board computers to acquire data and compute plant vigor metrics per plot. The supporting IT systems enable automatic path planning, plot identification, image and point cloud data QA/QC and near real-time analysis where results are streamed to enterprise databases for additional statistical analysis and product advancement decisions. Since the rover program was launched in North America in 2013, the number of research plots we can analyze in a growing season has expanded dramatically. This work describes some of the successes and challenges in scaling up of the rover platform for automated phenotyping to enable science at scale.
机译:作物改良计划需要大量细致的甄选过程,有效地,准确地收集和分析数据,生成优质的植物产品尽可能高效,制定优越的裁剪和/或作物改良方法。通常,用于这种测试数据的收集是通过使用手持式仪器或手动控制的设备场队进行。尽管采取步骤以减少误差,在这样的方式收集到的数据可能是不可靠由于人为错误和疲劳,这降低做出准确的选择决定的能力。孟山都的工程团队已经开发出一种高间隙移动平台(流动站)作为在工业规模实现高通量,高精度表型的一步。流动站都配备有GPS导航,多个摄像机和传感器和机载计算机采集数据和每个小区计算植物活力指标。支撑IT系统能够自动规划路径,情节识别,图像和点云数据QA / QC并在结果传输到企业数据库额外的统计分析和产品发展决策近乎实时的分析。由于月球车计划在2013年北美推出,研究地块我们可以在一个生长季节分析的数量急剧扩大。这部作品描述了用于自动化表型分型在规模,使科学流动站平台扩大一些成功和挑战的。

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